🤖 ws-bom-robot-app

A FastAPI application serving ws bom/robot/llm platform ai

🌵 Minimal app structure

app/
|-- .env
|-- main.py

Fill main.py with the following code:

from ws_bom_robot_app import main
app = main.app

Create a .env file in the root directory with the following configuration:

# robot configuration
robot_env=development
robot_user=your_username
USER_AGENT=ws-bom-robot-app

# cms (bowl) configuration
robot_cms_host='http://localhost:4000'
robot_cms_auth='users API-Key your-api-key-here'

# llm providers: fill one or more of these with your API keys
DEEPSEEK_API_KEY="your-deepseek-api-key"
OPENAI_API_KEY="your-openai-api-key"
GOOGLE_API_KEY="your-google-api-key"
ANTHROPIC_API_KEY="your-anthropic-api-key"
GROQ_API_KEY="your-groq-api-key"
# ibm
WATSONX_URL="https://eu-gb.ml.cloud.ibm.com"
WATSONX_APIKEY="your-watsonx-api-key"
WATSONX_PROJECTID="your-watsonx-project-id"
# gvertex: ensure to mount the file in docker
GOOGLE_APPLICATION_CREDENTIALS="./.data/secrets/google-credentials.json"

🚀 Run the app

development

fastapi dev --port 6001
#uvicorn main:app --app-dir ./ws_bom_robot_app --reload --reload-dir ws_bom_robot_app --host 0.0.0.0 --port 6001
#uvicorn main:app --app-dir ./ws_bom_robot_app --host 0.0.0.0 --port 6001

production

uvicorn main:app --host 0.0.0.0 --port 6001

production with multipler workers

fastapi run --port 6001 --workers 4
#uvicorn main:app --host 0.0.0.0 --port 6001 --workers 4
#gunicorn -w 4 -k uvicorn.workers.UvicornWorker main:app --bind

📖 API documentation

🐳 Docker

dockerize base image

<# cpu #>
docker build -f Dockerfile-robot-base-cpu -t ws-bom-robot-base:cpu .
docker tag ws-bom-robot-base:cpu ghcr.io/websolutespa/ws-bom-robot-base:cpu
docker push ghcr.io/websolutespa/ws-bom-robot-base:cpu
<# gpu #>
docker build -f Dockerfile-robot-base-gpu -t ws-bom-robot-base:gpu .
docker tag ws-bom-robot-base:gpu ghcr.io/websolutespa/ws-bom-robot-base:gpu
docker push ghcr.io/websolutespa/ws-bom-robot-base:gpu

dockerize app (from src)

docker build -f Dockerfile -t ws-bom-robot-app:cpu --build-arg DEVICE=cpu .
docker run --rm -d --name ws-bom-robot-app --env-file .env -p 6001:6001 ws-bom-robot-app:cpu

docker build -f Dockerfile -t ws-bom-robot-app:gpu --build-arg DEVICE=gpu .
docker run --rm -d --name ws-bom-robot-app --gpus all --env-file .env -p 6001:6001 ws-bom-robot-app:gpu

dockerize app (from latest)

docker build -f Dockerfile-pkg -t ws-bom-robot-app-pkg:cpu --build-arg DEVICE=cpu .
docker run --rm -d --name ws-bom-robot-app-pkg --env-file .env -p 6001:6001 ws-bom-robot-app-pkg:cpu

docker build -f Dockerfile-pkg -t ws-bom-robot-app-pkg:gpu --build-arg DEVICE=gpu .
docker run --rm -d --name ws-bom-robot-app-pkg --gpus all --env-file .env -p 6001:6001 ws-bom-robot-app-pkg:gpu
<# test gpu: nvidia-smi #>

docker run mounted to src (dev mode)

docker run --rm  -d --env-file .env -v "$(pwd)/.data:/app/.data" -p 6001:6001 ws-bom-robot-app fastapi dev ./ws_bom_robot_app/main.py --host 0.0.0.0 --port 6001
docker run --rm  -d --env-file .env -v "$(pwd)/.data:/app/.data" -p 6001:6001 ws-bom-robot-app uvicorn ws_bom_robot_app.main:app --reload --host 0.0.0.0 --port 6001

🔖 Windows requirements (for RAG functionality only)

⚠️ While it's strongly recommended to use a docker container for development, you can run the app on Windows with the following requirements

libmagic (mandatory)

  py -m pip install --upgrade python-magic-bin

tesseract-ocr (mandatory)

Install tesseract Last win-64 release

Add tesseract executable (C:\Program Files\Tesseract-OCR) to system PATH

  $pathToAdd = "C:\Program Files\Tesseract-OCR"; `
  $currentPath = [System.Environment]::GetEnvironmentVariable("Path", [System.EnvironmentVariableTarget]::Machine); `
  if ($currentPath -split ';' -notcontains $pathToAdd) { `
    [System.Environment]::SetEnvironmentVariable("Path", "$currentPath;$pathToAdd", [System.EnvironmentVariableTarget]::Machine) `
  }

docling

Set the following environment variables

  KMP_DUPLICATE_LIB_OK=TRUE

libreoffice (optional: for robot_env set to development/production)

Install libreoffice Last win-64 release

Add libreoffice executable (C:\Program Files\LibreOffice\program) to system PATH

  $pathToAdd = "C:\Program Files\LibreOffice\program"; `
  $currentPath = [System.Environment]::GetEnvironmentVariable("Path", [System.EnvironmentVariableTarget]::Machine); `
  if ($currentPath -split ';' -notcontains $pathToAdd) { `
    [System.Environment]::SetEnvironmentVariable("Path", "$currentPath;$pathToAdd", [System.EnvironmentVariableTarget]::Machine) `
  }

poppler (optional: for robot_env set to development/production)

Download win poppler release Extract the zip, copy the nested folder "poppler-x.x.x." to a program folder (e.g. C:\Program Files\poppler-24.08.0) Add poppler executable (C:\Program Files\poppler-24.08.0\Library\bin) to system PATH

  $pathToAdd = "C:\Program Files\poppler-24.08.0\Library\bin"; `
  $currentPath = [System.Environment]::GetEnvironmentVariable("Path", [System.EnvironmentVariableTarget]::Machine); `
  if ($currentPath -split ';' -notcontains $pathToAdd) { `
    [System.Environment]::SetEnvironmentVariable("Path", "$currentPath;$pathToAdd", [System.EnvironmentVariableTarget]::Machine) `
  }

👷 Contributors

Build/distribute pkg from websolutespa bom [Github]

dir in robot project folder

  cd ./src/robot

🔖 requirements

install uv venv package management

py -m pip install --upgrade uv
# create venv
uv venv
# activate venv
#win: .venv/Scripts/activate
#linux: source .venv/bin/activate

project requirements update

uv pip install --upgrade -r requirements.txt

build tools

uv pip install --upgrade setuptools build twine streamlit

🪛 build

clean dist and build package

if (Test-Path ./dist) {rm ./dist -r -force}; `
py -m build && twine check dist/*

linux/mac

[ -d ./dist ] && rm -rf ./dist
python -m build && twine check dist/*

📦 test / 🧪 debugger

Install the package in editable project location

uv pip install -U -e .
uv pip show ws-bom-robot-app

code quality tools

# .\src\robot
uv pip install -U scanreq prospector[with_everything]
## unused requirements
scanreq -r requirements.txt -p ./ws_bom_robot_app
## style/linting
prospector ./ws_bom_robot_app -t pylint -t pydocstyle
## code quality/complexity
prospector ./ws_bom_robot_app -t vulture -t mccabe -t mypy
## security
prospector ./ws_bom_robot_app -t dodgy -t bandit
## package
prospector ./ws_bom_robot_app -t pyroma

🧪 run tests

uv pip install -U pytest pytest-asyncio pytest-mock pytest-cov pyclean
# clean cache if needed
# pyclean --verbose .
pytest --cov=ws_bom_robot_app --log-cli-level=info
# directory
# pytest --cov=ws_bom_robot_app.llm.vector_store --log-cli-level=info ./tests/app/llm/vector_store

🐞 start debugger

streamlit run debugger.py --server.port 8051

✈️ publish

testpypi

twine upload --verbose -r testpypi dist/*
#pip install -i https://test.pypi.org/simple/ -U ws-bom-robot-app

pypi
```
twine upload --verbose dist/*
```

Metadata

Release files for ws-bom-robot-app 0.0.137

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for ws-bom-robot-app 0.0.137
File	Size	Uploaded
ws_bom_robot_app-0.0.137.tar.gz	114.4 kB	Oct 16, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for ws-bom-robot-app 0.0.137
File	Interpreter	ABI	Platform	Reset
ws_bom_robot_app-0.0.137-py3-none-any.whl 144.8 kB Oct 16, 2026	Python 3	none	any	Details

Total release size: 259.1 kB

Release files / ws_bom_robot_app-0.0.137.tar.gz

Download URL	ws_bom_robot_app-0.0.137.tar.gz
Size	114.4 kB
Tags	Source
SHA-256 checksum How to use checksums	`45ed0a71d28f27970d86e3f1cfd4301a181d3801fb7a7f9276b197c55332302b`
BLAKE2b-256 checksum How to use checksums	`df91cb03628a405eb4e02a5769f99554eb2755cfe4ffd2d3487a0b72f12d3afd`
Upload date	Oct 16, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.2.0 CPython/3.12.7`

Release files / ws_bom_robot_app-0.0.137-py3-none-any.whl

Download URL	ws_bom_robot_app-0.0.137-py3-none-any.whl
Size	144.8 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`23ef497c0032eee998458824ebb0b7224b12cb9791d65530038849e51c7afd8e`
BLAKE2b-256 checksum How to use checksums	`581771882534ff56998b9a65185346f734aaa701ce08a7b3e314d99b330998ba`
Upload date	Oct 16, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.2.0 CPython/3.12.7`